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NCT05898165: FIND-AF

Future Innovations in Novel Detection for Atrial Fibrillation (FIND-AF): Pilot Study

Active, enrolled Last updated 17 September 2025
What this trial tests

trial testing Development of an algorithm in Atrial Fibrillation in 1,955 participants. Participants enrolled and being followed up; not accepting new ones.

Timeline
1 October 2023
Primary endpoint
16 June 2025
28 February 2026

Quick facts

Lead sponsorUniversity of Leeds
StatusActive, enrolled
Study typeOBSERVATIONAL
Enrollment1,955
Start date1 October 2023
Primary completion16 June 2025
Estimated completion28 February 2026
Sites1 location across United Kingdom

Drugs / interventions tested

Conditions studied

Sponsor

University of Leeds

Who can join

30 and older, any sex, with Atrial Fibrillation or Heart Diseases. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The purpose of this study is to trial a new intervention - risk-guided AF screening using an EHR-based risk score and remote ECG monitoring process - and to characterise individuals at elevated predicted AF risk.

Publications & conference data

6 peer-reviewed publications reference this trial (live from Europe PMC):

  1. Future Innovations in Novel Detection for Atrial Fibrillation (FIND-AF): pilot study of an electronic health record machine learning algorithm-guided intervention to identify undiagnosed atrial fibrillation.
    Nadarajah R, Wahab A, Reynolds C, Raveendra K, et al · · 2023 · cited 11× · PMID 37777255 · DOI 10.1136/openhrt-2023-002447
  2. Phenotypic characterization of people at risk of atrial fibrillation: protocol for the FIND-AF longitudinal cohort study.
    Wahab A, Nadarajah R, Reynolds C, Bennett S, et al · · 2024 · cited 3× · PMID 39319414 · DOI 10.1093/eurjpc/zwae303
  3. Perceptions of healthcare professionals on the use of a risk prediction model to inform atrial fibrillation screening: qualitative interview study in English primary care.
    Hamilton E, Shone L, Reynolds C, Wu J, et al · · 2025 · cited 2× · PMID 39909527 · DOI 10.1136/bmjopen-2024-091675
  4. Towards improved detection of subclinical atrial fibrillation - Who could benefit from targeted screening?
    Fender AC, Dobrev D. · · 2024 · cited 1× · PMID 39911612 · DOI 10.1016/j.ijcha.2024.101550
  5. Cardiac magnetic resonance imaging-derived atrial fibrosis in patients with pre-atrial fibrillation.
    Wahab A, Nadarajah R, Tomoaia R, Javed W, et al · · 2025 · PMID 41314690 · DOI 10.1136/openhrt-2025-003747
  6. Protocol for the OPTIMSE-1 randomised clinical trial to test specialist-led identification and management of cardio-renal-metabolic-pulmonary disease in machine learning algorithm-detected high-risk community-dwelling individuals.
    Nadarajah R, Wahab A, Joseph T, Reynolds C, et al · · 2025 · PMID 40774703 · DOI 10.1136/bmjopen-2025-101088

Verify or expand the search:

Other trials of Development of an algorithm

Trials testing the same drug.

Other recruiting trials for Atrial Fibrillation

Currently open trials in the same condition.

Other University of Leeds trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT05898165.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing